Abstract
High-resolution subsea surveying offers new opportunities to explore difficult or hazardous underwater environments and, when using multi-beam sonar, provides three-dimensional bathymetric data for visualisation. The primary focus of this practice-led research is whether the 3D visualisation and grading of subsea survey data can be developed beyond current industry practices. Three commercial case studies and their resulting datasets were used: Troll, an oil and gas field near Norway; Greater Gabbard, an offshore wind farm near England; and Gullfaks, an oil and gas field near Norway.This investigation is structured using the author’s Explore Review Create methodology – an iterative multi-method approach with contributory elements including action research and reflective practice. The research is supported by an exploration and review of relevant literature, comparing existing visualisation techniques and identifying a lack of consistency in evaluating or grading subsea survey data. Three case studies follow, presenting and evaluating the application of a variety of 3D visualisation techniques including some which go beyond those readily adopted in the offshore industry, such as the use of 3D printing. Finally, a fourth research chapter examines how the state of data can be assessed and proposes a scale by which future data could be graded – the DUNDEE DATA GRADING SCALE.
The author proposes that the work undertaken during each of these three case studies provides new knowledge in improving the application of 3D visualisation techniques to subsea survey data. As a result of this new knowledge, the DUNDEE DATA GRADING SCALE is offered as a first step towards improving data capture and quality awareness by providing an improved understanding of what will be required to produce quality 3D visualisations from each dataset, with additional clarity in how to achieve this by applying a broader range of visualisation tools.
| Date of Award | 2020 |
|---|---|
| Original language | English |
| Sponsors | Engineering and Physical Sciences Research Council & ADUS Deepocean |
| Supervisor | Chris Rowland (Supervisor) & Jon Rogers (Supervisor) |